YData Profiling Report

Brought to you by YData

Dataset statistics

Number of variables	14
Number of observations	20,000
Missing cells	55,841
Missing cells (%)	19.9%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	33.2 MiB
Average record size in memory	1.7 KiB

Variable types

Numeric	1
Text	9
URL	1
Unsupported	2
DateTime	1

Alerts

`comments` has 2349 (11.7%) missing values	Missing
`journal-ref` has 9486 (47.4%) missing values	Missing
`doi` has 7396 (37.0%) missing values	Missing
`report-no` has 18106 (90.5%) missing values	Missing
`license` has 18504 (92.5%) missing values	Missing
`id` has unique values	Unique
`versions` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`authors_parsed` is an unsupported type, check if it needs cleaning or further analysis	Unsupported

Reproduction

Analysis started	2025-07-03 11:07:12.650355
Analysis finished	2025-07-03 11:08:35.436338
Duration	1 minute and 22.79 seconds
Software version	ydata-profiling vv4.16.1
Download configuration	config.json

id
Real number (ℝ)

Unique

Distinct	20000
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	706.02589

Minimum	704.0001
Maximum	708.2148
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	156.4 KiB

Quantile statistics

Minimum	704.0001
5-th percentile	704.1001
Q1	705.09977
median	706.13135
Q3	707.18293
95-th percentile	708.1148
Maximum	708.2148
Range	4.2147
Interquartile range (IQR)	2.08315

Descriptive statistics

Standard deviation	1.282659
Coefficient of variation (CV)	0.0018167308
Kurtosis	-1.1709981
Mean	706.02589
Median Absolute Deviation (MAD)	1.0416
Skewness	0.021111905
Sum	14120518
Variance	1.6452141
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
704.0001	1	< 0.1%
707.016	1	< 0.1%
707.0167	1	< 0.1%
707.0166	1	< 0.1%
707.0165	1	< 0.1%
707.0164	1	< 0.1%
707.0163	1	< 0.1%
707.0162	1	< 0.1%
707.0161	1	< 0.1%
707.0159	1	< 0.1%
Other values (19990)	19990	> 99.9%

Value	Count	Frequency (%)
704.0001	1	< 0.1%
704.0002	1	< 0.1%
704.0003	1	< 0.1%
704.0004	1	< 0.1%
704.0005	1	< 0.1%
704.0006	1	< 0.1%
704.0007	1	< 0.1%
704.0008	1	< 0.1%
704.0009	1	< 0.1%
704.001	1	< 0.1%

Value	Count	Frequency (%)
708.2148	1	< 0.1%
708.2147	1	< 0.1%
708.2146	1	< 0.1%
708.2145	1	< 0.1%
708.2144	1	< 0.1%
708.2143	1	< 0.1%
708.2142	1	< 0.1%
708.2141	1	< 0.1%
708.214	1	< 0.1%
708.2139	1	< 0.1%

submitter
Text

Distinct	14553
Distinct (%)	72.8%
Missing	0
Missing (%)	0.0%
Memory size	1.2 MiB

Length

Max length	45
Median length	41
Mean length	14.79595
Min length	3

Characters and Unicode

Total characters	295,919
Distinct characters	73
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	11,068 ?
Unique (%)	55.3%

Sample

1st row	Pavel Nadolsky
2nd row	Louis Theran
3rd row	Hongjun Pan
4th row	David Callan
5th row	Alberto Torchinsky

Value	Count	Frequency (%)
dr	337	0.8%
a	323	0.7%
michael	275	0.6%
m	273	0.6%
david	220	0.5%
j	210	0.5%
alexander	203	0.5%
de	190	0.4%
s	185	0.4%
thomas	159	0.4%
Other values (16446)	42269	94.7%

Most occurring characters

Value	Count	Frequency (%)
a	29254	9.9%
	24675	8.3%
e	22834	7.7%
i	21459	7.3%
n	19240	6.5%
r	18175	6.1%
o	17141	5.8%
l	11354	3.8%
s	10072	3.4%
t	9127	3.1%
Other values (63)	112588	38.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	295919	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
a	29254	9.9%
	24675	8.3%
e	22834	7.7%
i	21459	7.3%
n	19240	6.5%
r	18175	6.1%
o	17141	5.8%
l	11354	3.8%
s	10072	3.4%
t	9127	3.1%
Other values (63)	112588	38.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	295919	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
a	29254	9.9%
	24675	8.3%
e	22834	7.7%
i	21459	7.3%
n	19240	6.5%
r	18175	6.1%
o	17141	5.8%
l	11354	3.8%
s	10072	3.4%
t	9127	3.1%
Other values (63)	112588	38.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	295919	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
a	29254	9.9%
	24675	8.3%
e	22834	7.7%
i	21459	7.3%
n	19240	6.5%
r	18175	6.1%
o	17141	5.8%
l	11354	3.8%
s	10072	3.4%
t	9127	3.1%
Other values (63)	112588	38.0%

authors
Text

Distinct	18434
Distinct (%)	92.2%
Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

Length

Max length	1,467
Median length	792
Mean length	55.96375
Min length	4

Characters and Unicode

Total characters	1,119,275
Distinct characters	87
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	17,327 ?
Unique (%)	86.6%

Sample

1st row	C. Bal\'azs, E. L. Berger, P. M. Nadolsky, C.-P. Yuan
2nd row	Ileana Streinu and Louis Theran
3rd row	Hongjun Pan
4th row	David Callan
5th row	Wael Abu-Shammala and Alberto Torchinsky

Value	Count	Frequency (%)
and	7452	4.3%
a	4078	2.3%
m	3751	2.1%
j	3162	1.8%
s	2700	1.5%
r	2121	1.2%
1	2103	1.2%
p	1927	1.1%
d	1895	1.1%
c	1853	1.1%
Other values (38170)	143610	82.2%

Most occurring characters

Value	Count	Frequency (%)
	161039	14.4%
a	84685	7.6%
e	64871	5.8%
n	60772	5.4%
i	59275	5.3%
.	49793	4.4%
o	49467	4.4%
r	49455	4.4%
,	41798	3.7%
l	30956	2.8%
Other values (77)	467164	41.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1119275	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	161039	14.4%
a	84685	7.6%
e	64871	5.8%
n	60772	5.4%
i	59275	5.3%
.	49793	4.4%
o	49467	4.4%
r	49455	4.4%
,	41798	3.7%
l	30956	2.8%
Other values (77)	467164	41.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1119275	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	161039	14.4%
a	84685	7.6%
e	64871	5.8%
n	60772	5.4%
i	59275	5.3%
.	49793	4.4%
o	49467	4.4%
r	49455	4.4%
,	41798	3.7%
l	30956	2.8%
Other values (77)	467164	41.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1119275	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	161039	14.4%
a	84685	7.6%
e	64871	5.8%
n	60772	5.4%
i	59275	5.3%
.	49793	4.4%
o	49467	4.4%
r	49455	4.4%
,	41798	3.7%
l	30956	2.8%
Other values (77)	467164	41.7%

title
Text

Distinct	19989
Distinct (%)	99.9%
Missing	0
Missing (%)	0.0%
Memory size	2.3 MiB

Length

Max length	231
Median length	172
Mean length	70.51015
Min length	8

Characters and Unicode

Total characters	1,410,203
Distinct characters	96
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	19,983 ?
Unique (%)	99.9%

Sample

1st row	Calculation of prompt diphoton production cross sections at Tevatron and LHC energies
2nd row	Sparsity-certifying Graph Decompositions
3rd row	The evolution of the Earth-Moon system based on the dark matter field fluid model
4th row	A determinant of Stirling cycle numbers counts unlabeled acyclic single-source automata
5th row	From dyadic $\Lambda_{\alpha}$ to $\Lambda_{\alpha}$

Value	Count	Frequency (%)
of	11705	6.1%
the	9183	4.8%
in	6781	3.5%
and	6353	3.3%
a	4006	2.1%
for	3052	1.6%
on	2591	1.4%
with	1926	1.0%
to	1345	0.7%
quantum	1316	0.7%
Other values (21516)	143033	74.8%

Most occurring characters

Value	Count	Frequency (%)
	179633	12.7%
e	115238	8.2%
i	98866	7.0%
n	94186	6.7%
o	94138	6.7%
a	92750	6.6%
t	91450	6.5%
r	75557	5.4%
s	68801	4.9%
l	51838	3.7%
Other values (86)	447746	31.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1410203	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	179633	12.7%
e	115238	8.2%
i	98866	7.0%
n	94186	6.7%
o	94138	6.7%
a	92750	6.6%
t	91450	6.5%
r	75557	5.4%
s	68801	4.9%
l	51838	3.7%
Other values (86)	447746	31.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1410203	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	179633	12.7%
e	115238	8.2%
i	98866	7.0%
n	94186	6.7%
o	94138	6.7%
a	92750	6.6%
t	91450	6.5%
r	75557	5.4%
s	68801	4.9%
l	51838	3.7%
Other values (86)	447746	31.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1410203	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	179633	12.7%
e	115238	8.2%
i	98866	7.0%
n	94186	6.7%
o	94138	6.7%
a	92750	6.6%
t	91450	6.5%
r	75557	5.4%
s	68801	4.9%
l	51838	3.7%
Other values (86)	447746	31.8%

comments
Text

Missing

Distinct	13002
Distinct (%)	73.7%
Missing	2349
Missing (%)	11.7%
Memory size	1.9 MiB

Length

Max length	408
Median length	345
Mean length	61.106056
Min length	1

Characters and Unicode

Total characters	1,078,583
Distinct characters	94
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	12,312 ?
Unique (%)	69.8%

Sample

1st row	37 pages, 15 figures; published version
2nd row	To appear in Graphs and Combinatorics
3rd row	23 pages, 3 figures
4th row	11 pages
5th row	6 pages, 4 figures, accepted by PRA

Value	Count	Frequency (%)
pages	14445	8.5%
figures	9705	5.7%
in	6074	3.6%
to	4406	2.6%
the	4245	2.5%
4	3158	1.8%
of	3096	1.8%
and	2986	1.7%
accepted	2516	1.5%
version	2347	1.4%
Other values (9981)	117957	69.0%

Most occurring characters

Value	Count	Frequency (%)
	160796	14.9%
e	98839	9.2%
s	62072	5.8%
a	58851	5.5%
i	58344	5.4%
r	50350	4.7%
t	49688	4.6%
n	45841	4.3%
o	45771	4.2%
p	37606	3.5%
Other values (84)	410425	38.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	1078583	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	160796	14.9%
e	98839	9.2%
s	62072	5.8%
a	58851	5.5%
i	58344	5.4%
r	50350	4.7%
t	49688	4.6%
n	45841	4.3%
o	45771	4.2%
p	37606	3.5%
Other values (84)	410425	38.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	1078583	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	160796	14.9%
e	98839	9.2%
s	62072	5.8%
a	58851	5.5%
i	58344	5.4%
r	50350	4.7%
t	49688	4.6%
n	45841	4.3%
o	45771	4.2%
p	37606	3.5%
Other values (84)	410425	38.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	1078583	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	160796	14.9%
e	98839	9.2%
s	62072	5.8%
a	58851	5.5%
i	58344	5.4%
r	50350	4.7%
t	49688	4.6%
n	45841	4.3%
o	45771	4.2%
p	37606	3.5%
Other values (84)	410425	38.1%

journal-ref
Text

Missing

Distinct	10458
Distinct (%)	99.5%
Missing	9486
Missing (%)	47.4%
Memory size	1.2 MiB

Length

Max length	237
Median length	211
Mean length	37.046034
Min length	9

Characters and Unicode

Total characters	389,502
Distinct characters	90
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	10,444 ?
Unique (%)	99.3%

Sample

1st row	Phys.Rev.D76:013009,2007
2nd row	Illinois J. Math. 52 (2008) no.2, 681-689
3rd row	Phys.Rev.D76:044016,2007
4th row	Journal of Applied Physics, vol 104, 073536 (2008)
5th row	Astrophys.J.663:1149-1173,2007

Value	Count	Frequency (%)
2007	2696	5.7%
phys	2158	4.6%
rev	1443	3.1%
2008	1440	3.1%
j	840	1.8%
b	767	1.6%
76	745	1.6%
of	744	1.6%
a	615	1.3%
lett	563	1.2%
Other values (13615)	34884	74.4%

Most occurring characters

Value	Count	Frequency (%)
	37194	9.5%
0	34035	8.7%
.	21469	5.5%
2	19865	5.1%
7	15370	3.9%
1	14044	3.6%
e	12985	3.3%
s	12621	3.2%
,	12274	3.2%
o	11013	2.8%
Other values (80)	198632	51.0%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	389502	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	37194	9.5%
0	34035	8.7%
.	21469	5.5%
2	19865	5.1%
7	15370	3.9%
1	14044	3.6%
e	12985	3.3%
s	12621	3.2%
,	12274	3.2%
o	11013	2.8%
Other values (80)	198632	51.0%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	389502	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	37194	9.5%
0	34035	8.7%
.	21469	5.5%
2	19865	5.1%
7	15370	3.9%
1	14044	3.6%
e	12985	3.3%
s	12621	3.2%
,	12274	3.2%
o	11013	2.8%
Other values (80)	198632	51.0%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	389502	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	37194	9.5%
0	34035	8.7%
.	21469	5.5%
2	19865	5.1%
7	15370	3.9%
1	14044	3.6%
e	12985	3.3%
s	12621	3.2%
,	12274	3.2%
o	11013	2.8%
Other values (80)	198632	51.0%

doi
Text

Missing

Distinct	12593
Distinct (%)	99.9%
Missing	7396
Missing (%)	37.0%
Memory size	1.1 MiB

Length

Max length	82
Median length	61
Mean length	25.188194
Min length	10

Characters and Unicode

Total characters	317,472
Distinct characters	76
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	12,584 ?
Unique (%)	99.8%

Sample

1st row	10.1103/PhysRevD.76.013009
2nd row	10.1103/PhysRevA.75.043613
3rd row	10.1103/PhysRevD.76.044016
4th row	10.1063/1.2975338
5th row	10.1086/518646

Value	Count	Frequency (%)
10.1103/physrevlett.99.071302	4	< 0.1%
10.1088/0954-3899/35/5/054001	2	< 0.1%
10.1111/j.1365-2966.2007.12016.x	2	< 0.1%
10.1086/519272	2	< 0.1%
10.1016/j.jcp.2007.08.023	2	< 0.1%
10.1142/s0218301307008410	2	< 0.1%
10.1088/1751-8113/40/40/012	2	< 0.1%
10.1088/0953-8984/20/7/075103	2	< 0.1%
10.1063/1.2775909	2	< 0.1%
10.1086/518714	2	< 0.1%
Other values (12649)	12649	99.8%

Most occurring characters

Value	Count	Frequency (%)
0	58539	18.4%
1	52061	16.4%
.	30054	9.5%
/	18045	5.7%
2	16090	5.1%
7	15491	4.9%
6	14274	4.5%
3	14186	4.5%
8	11677	3.7%
5	9888	3.1%
Other values (66)	77167	24.3%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	317472	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	58539	18.4%
1	52061	16.4%
.	30054	9.5%
/	18045	5.7%
2	16090	5.1%
7	15491	4.9%
6	14274	4.5%
3	14186	4.5%
8	11677	3.7%
5	9888	3.1%
Other values (66)	77167	24.3%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	317472	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	58539	18.4%
1	52061	16.4%
.	30054	9.5%
/	18045	5.7%
2	16090	5.1%
7	15491	4.9%
6	14274	4.5%
3	14186	4.5%
8	11677	3.7%
5	9888	3.1%
Other values (66)	77167	24.3%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	317472	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	58539	18.4%
1	52061	16.4%
.	30054	9.5%
/	18045	5.7%
2	16090	5.1%
7	15491	4.9%
6	14274	4.5%
3	14186	4.5%
8	11677	3.7%
5	9888	3.1%
Other values (66)	77167	24.3%

report-no
Text

Missing

Distinct	1886
Distinct (%)	99.6%
Missing	18106
Missing (%)	90.5%
Memory size	692.4 KiB

Length

Max length	130
Median length	91
Mean length	19.375396
Min length	4

Characters and Unicode

Total characters	36,697
Distinct characters	83
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1,881 ?
Unique (%)	99.3%

Sample

1st row	ANL-HEP-PR-07-12
2nd row	IGPG-07/03-2
3rd row	LA-UR-07-2051, LLNL-JRNL-410358
4th row	BABAR-PUB-07/015, SLAC-PUB-12417
5th row	Published in Systemics of Emergence. Research and Development, Minati G., Pessa E., Abram M., Springer, 2006, pages 723-734

Value	Count	Frequency (%)
desy	55	1.7%
preprint	43	1.3%
lmu-asc	23	0.7%
report	20	0.6%
	14	0.4%
of	13	0.4%
clns	13	0.4%
cleo	13	0.4%
university	12	0.4%
mit-ctp	10	0.3%
Other values (2742)	3032	93.3%

Most occurring characters

Value	Count	Frequency (%)
-	4483	12.2%
0	3740	10.2%
7	2260	6.2%
P	1693	4.6%
2	1476	4.0%
	1368	3.7%
1	1325	3.6%
T	1256	3.4%
/	1180	3.2%
S	1165	3.2%
Other values (73)	16751	45.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	36697	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
-	4483	12.2%
0	3740	10.2%
7	2260	6.2%
P	1693	4.6%
2	1476	4.0%
	1368	3.7%
1	1325	3.6%
T	1256	3.4%
/	1180	3.2%
S	1165	3.2%
Other values (73)	16751	45.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	36697	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
-	4483	12.2%
0	3740	10.2%
7	2260	6.2%
P	1693	4.6%
2	1476	4.0%
	1368	3.7%
1	1325	3.6%
T	1256	3.4%
/	1180	3.2%
S	1165	3.2%
Other values (73)	16751	45.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	36697	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
-	4483	12.2%
0	3740	10.2%
7	2260	6.2%
P	1693	4.6%
2	1476	4.0%
	1368	3.7%
1	1325	3.6%
T	1256	3.4%
/	1180	3.2%
S	1165	3.2%
Other values (73)	16751	45.6%

categories
Text

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Distinct (%)	11.0%
Missing	0
Missing (%)	0.0%
Memory size	1.2 MiB

Length

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Median length	94
Mean length	14.08775
Min length	5

Characters and Unicode

Total characters	281,755
Distinct characters	45
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1,323 ?
Unique (%)	6.6%

Sample

1st row	hep-ph
2nd row	math.CO cs.CG
3rd row	physics.gen-ph
4th row	math.CO
5th row	math.CA math.FA

Value	Count	Frequency (%)
astro-ph	4044	13.4%
hep-th	1907	6.3%
hep-ph	1882	6.3%
quant-ph	1342	4.5%
gr-qc	1109	3.7%
cond-mat.mtrl-sci	930	3.1%
cond-mat.str-el	883	2.9%
cond-mat.stat-mech	881	2.9%
math-ph	870	2.9%
math.mp	870	2.9%
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Most occurring characters

Value	Count	Frequency (%)
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t	27492	9.8%
-	24788	8.8%
a	21981	7.8%
.	17385	6.2%
p	17243	6.1%
m	16648	5.9%
s	15630	5.5%
c	13882	4.9%
o	12359	4.4%
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Most occurring categories

Value	Count	Frequency (%)
(unknown)	281755	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
h	29176	10.4%
t	27492	9.8%
-	24788	8.8%
a	21981	7.8%
.	17385	6.2%
p	17243	6.1%
m	16648	5.9%
s	15630	5.5%
c	13882	4.9%
o	12359	4.4%
Other values (35)	85171	30.2%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	281755	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
h	29176	10.4%
t	27492	9.8%
-	24788	8.8%
a	21981	7.8%
.	17385	6.2%
p	17243	6.1%
m	16648	5.9%
s	15630	5.5%
c	13882	4.9%
o	12359	4.4%
Other values (35)	85171	30.2%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	281755	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
h	29176	10.4%
t	27492	9.8%
-	24788	8.8%
a	21981	7.8%
.	17385	6.2%
p	17243	6.1%
m	16648	5.9%
s	15630	5.5%
c	13882	4.9%
o	12359	4.4%
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license
URL

Missing

Distinct	8
Distinct (%)	0.5%
Missing	18504
Missing (%)	92.5%
Memory size	724.4 KiB

http://arxiv.org/licenses/nonexclusive-distrib/1.0/	1472
http://creativecommons.org/licenses/by/4.0/	9
http://creativecommons.org/licenses/by-nc-sa/3.0/	5
http://creativecommons.org/licenses/publicdomain/	3
http://creativecommons.org/licenses/by/3.0/	3
Other values (3)	4
(Missing)	18504

Value	Count	Frequency (%)
http://arxiv.org/licenses/nonexclusive-distrib/1.0/	1472	7.4%
http://creativecommons.org/licenses/by/4.0/	9	< 0.1%
http://creativecommons.org/licenses/by-nc-sa/3.0/	5	< 0.1%
http://creativecommons.org/licenses/publicdomain/	3	< 0.1%
http://creativecommons.org/licenses/by/3.0/	3	< 0.1%
http://creativecommons.org/licenses/by-nc-nd/4.0/	2	< 0.1%
http://creativecommons.org/licenses/by-sa/4.0/	1	< 0.1%
http://creativecommons.org/licenses/by-nc-sa/4.0/	1	< 0.1%
(Missing)	18504	92.5%

Value	Count	Frequency (%)
http	1496	7.5%
(Missing)	18504	92.5%

Value	Count	Frequency (%)
arxiv.org	1472	7.4%
creativecommons.org	24	0.1%
(Missing)	18504	92.5%

Value	Count	Frequency (%)
/licenses/nonexclusive-distrib/1.0/	1472	7.4%
/licenses/by/4.0/	9	< 0.1%
/licenses/by-nc-sa/3.0/	5	< 0.1%
/licenses/publicdomain/	3	< 0.1%
/licenses/by/3.0/	3	< 0.1%
/licenses/by-nc-nd/4.0/	2	< 0.1%
/licenses/by-sa/4.0/	1	< 0.1%
/licenses/by-nc-sa/4.0/	1	< 0.1%
(Missing)	18504	92.5%

Value	Count	Frequency (%)
	1496	7.5%
(Missing)	18504	92.5%

Value	Count	Frequency (%)
	1496	7.5%
(Missing)	18504	92.5%

abstract
Text

Distinct	19979
Distinct (%)	99.9%
Missing	0
Missing (%)	0.0%
Memory size	16.2 MiB

Length

Max length	2,034
Median length	1,390
Mean length	801.3511
Min length	20

Characters and Unicode

Total characters	16,027,022
Distinct characters	96
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	19,966 ?
Unique (%)	99.8%

Sample

1st row	A fully differential calculation in perturbative quantum chromodynamics is presented for the production of massive photon pairs at hadron colliders. All next-to-leading order perturbative contributions from quark-antiquark, gluon-(anti)quark, and gluon-gluon subprocesses are included, as well as all-orders resummation of initial-state gluon radiation valid at next-to-next-to-leading logarithmic accuracy. The region of phase space is specified in which the calculation is most reliable. Good agreement is demonstrated with data from the Fermilab Tevatron, and predictions are made for more detailed tests with CDF and DO data. Predictions are shown for distributions of diphoton pairs produced at the energy of the Large Hadron Collider (LHC). Distributions of the diphoton pairs from the decay of a Higgs boson are contrasted with those produced from QCD processes at the LHC, showing that enhanced sensitivity to the signal can be obtained with judicious selection of events.
2nd row	We describe a new algorithm, the $(k,\ell)$-pebble game with colors, and use it obtain a characterization of the family of $(k,\ell)$-sparse graphs and algorithmic solutions to a family of problems concerning tree decompositions of graphs. Special instances of sparse graphs appear in rigidity theory and have received increased attention in recent years. In particular, our colored pebbles generalize and strengthen the previous results of Lee and Streinu and give a new proof of the Tutte-Nash-Williams characterization of arboricity. We also present a new decomposition that certifies sparsity based on the $(k,\ell)$-pebble game with colors. Our work also exposes connections between pebble game algorithms and previous sparse graph algorithms by Gabow, Gabow and Westermann and Hendrickson.
3rd row	The evolution of Earth-Moon system is described by the dark matter field fluid model proposed in the Meeting of Division of Particle and Field 2004, American Physical Society. The current behavior of the Earth-Moon system agrees with this model very well and the general pattern of the evolution of the Moon-Earth system described by this model agrees with geological and fossil evidence. The closest distance of the Moon to Earth was about 259000 km at 4.5 billion years ago, which is far beyond the Roche's limit. The result suggests that the tidal friction may not be the primary cause for the evolution of the Earth-Moon system. The average dark matter field fluid constant derived from Earth-Moon system data is 4.39 x 10^(-22) s^(-1)m^(-1). This model predicts that the Mars's rotation is also slowing with the angular acceleration rate about -4.38 x 10^(-22) rad s^(-2).
4th row	We show that a determinant of Stirling cycle numbers counts unlabeled acyclic single-source automata. The proof involves a bijection from these automata to certain marked lattice paths and a sign-reversing involution to evaluate the determinant.
5th row	In this paper we show how to compute the $\Lambda_{\alpha}$ norm, $\alpha\ge 0$, using the dyadic grid. This result is a consequence of the description of the Hardy spaces $H^p(R^N)$ in terms of dyadic and special atoms.

Value	Count	Frequency (%)
the	196264	8.1%
of	116739	4.8%
a	62164	2.6%
and	59073	2.4%
in	54266	2.2%
to	45635	1.9%
we	37739	1.6%
is	36940	1.5%
for	28038	1.2%
that	25434	1.0%
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Most occurring characters

Value	Count	Frequency (%)
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i	1017751	6.4%
a	1011134	6.3%
o	950892	5.9%
n	922098	5.8%
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r	810388	5.1%
l	535188	3.3%
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Most occurring categories

Value	Count	Frequency (%)
(unknown)	16027022	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	2252000	14.1%
e	1553229	9.7%
t	1166718	7.3%
i	1017751	6.4%
a	1011134	6.3%
o	950892	5.9%
n	922098	5.8%
s	854614	5.3%
r	810388	5.1%
l	535188	3.3%
Other values (86)	4953010	30.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	16027022	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	2252000	14.1%
e	1553229	9.7%
t	1166718	7.3%
i	1017751	6.4%
a	1011134	6.3%
o	950892	5.9%
n	922098	5.8%
s	854614	5.3%
r	810388	5.1%
l	535188	3.3%
Other values (86)	4953010	30.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	16027022	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	2252000	14.1%
e	1553229	9.7%
t	1166718	7.3%
i	1017751	6.4%
a	1011134	6.3%
o	950892	5.9%
n	922098	5.8%
s	854614	5.3%
r	810388	5.1%
l	535188	3.3%
Other values (86)	4953010	30.9%

versions
Unsupported

Rejected Unsupported

Missing	0
Missing (%)	0.0%
Memory size	1.8 MiB

update_date
Date

Distinct	1875
Distinct (%)	9.4%
Missing	0
Missing (%)	0.0%
Memory size	156.4 KiB

Minimum	2007-05-23 00:00:00
Maximum	2025-06-16 00:00:00
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=50)

authors_parsed
Unsupported

Rejected Unsupported

Missing	0
Missing (%)	0.0%
Memory size	2.0 MiB

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

	id	submitter	authors	title	comments	journal-ref	doi	report-no	categories	license	abstract	versions	update_date	authors_parsed
0	704.0001	Pavel Nadolsky	C. Bal\'azs, E. L. Berger, P. M. Nadolsky, C.-P. Yuan	Calculation of prompt diphoton production cross sections at Tevatron and\n LHC energies	37 pages, 15 figures; published version	Phys.Rev.D76:013009,2007	10.1103/PhysRevD.76.013009	ANL-HEP-PR-07-12	hep-ph	None	A fully differential calculation in perturbative quantum chromodynamics is\npresented for the production of massive photon pairs at hadron colliders. All\nnext-to-leading order perturbative contributions from quark-antiquark,\ngluon-(anti)quark, and gluon-gluon subprocesses are included, as well as\nall-orders resummation of initial-state gluon radiation valid at\nnext-to-next-to-leading logarithmic accuracy. The region of phase space is\nspecified in which the calculation is most reliable. Good agreement is\ndemonstrated with data from the Fermilab Tevatron, and predictions are made for\nmore detailed tests with CDF and DO data. Predictions are shown for\ndistributions of diphoton pairs produced at the energy of the Large Hadron\nCollider (LHC). Distributions of the diphoton pairs from the decay of a Higgs\nboson are contrasted with those produced from QCD processes at the LHC, showing\nthat enhanced sensitivity to the signal can be obtained with judicious\nselection of events.\n	[{'version': 'v1', 'created': 'Mon, 2 Apr 2007 19:18:42 GMT'}, {'version': 'v2', 'created': 'Tue, 24 Jul 2007 20:10:27 GMT'}]	2008-11-26	[[Balázs, C., ], [Berger, E. L., ], [Nadolsky, P. M., ], [Yuan, C. -P., ]]
1	704.0002	Louis Theran	Ileana Streinu and Louis Theran	Sparsity-certifying Graph Decompositions	To appear in Graphs and Combinatorics	None	None	None	math.CO cs.CG	http://arxiv.org/licenses/nonexclusive-distrib/1.0/	We describe a new algorithm, the $(k,\ell)$-pebble game with colors, and use\nit obtain a characterization of the family of $(k,\ell)$-sparse graphs and\nalgorithmic solutions to a family of problems concerning tree decompositions of\ngraphs. Special instances of sparse graphs appear in rigidity theory and have\nreceived increased attention in recent years. In particular, our colored\npebbles generalize and strengthen the previous results of Lee and Streinu and\ngive a new proof of the Tutte-Nash-Williams characterization of arboricity. We\nalso present a new decomposition that certifies sparsity based on the\n$(k,\ell)$-pebble game with colors. Our work also exposes connections between\npebble game algorithms and previous sparse graph algorithms by Gabow, Gabow and\nWestermann and Hendrickson.\n	[{'version': 'v1', 'created': 'Sat, 31 Mar 2007 02:26:18 GMT'}, {'version': 'v2', 'created': 'Sat, 13 Dec 2008 17:26:00 GMT'}]	2008-12-13	[[Streinu, Ileana, ], [Theran, Louis, ]]
2	704.0003	Hongjun Pan	Hongjun Pan	The evolution of the Earth-Moon system based on the dark matter field\n fluid model	23 pages, 3 figures	None	None	None	physics.gen-ph	None	The evolution of Earth-Moon system is described by the dark matter field\nfluid model proposed in the Meeting of Division of Particle and Field 2004,\nAmerican Physical Society. The current behavior of the Earth-Moon system agrees\nwith this model very well and the general pattern of the evolution of the\nMoon-Earth system described by this model agrees with geological and fossil\nevidence. The closest distance of the Moon to Earth was about 259000 km at 4.5\nbillion years ago, which is far beyond the Roche's limit. The result suggests\nthat the tidal friction may not be the primary cause for the evolution of the\nEarth-Moon system. The average dark matter field fluid constant derived from\nEarth-Moon system data is 4.39 x 10^(-22) s^(-1)m^(-1). This model predicts\nthat the Mars's rotation is also slowing with the angular acceleration rate\nabout -4.38 x 10^(-22) rad s^(-2).\n	[{'version': 'v1', 'created': 'Sun, 1 Apr 2007 20:46:54 GMT'}, {'version': 'v2', 'created': 'Sat, 8 Dec 2007 23:47:24 GMT'}, {'version': 'v3', 'created': 'Sun, 13 Jan 2008 00:36:28 GMT'}]	2008-01-13	[[Pan, Hongjun, ]]
3	704.0004	David Callan	David Callan	A determinant of Stirling cycle numbers counts unlabeled acyclic\n single-source automata	11 pages	None	None	None	math.CO	None	We show that a determinant of Stirling cycle numbers counts unlabeled acyclic\nsingle-source automata. The proof involves a bijection from these automata to\ncertain marked lattice paths and a sign-reversing involution to evaluate the\ndeterminant.\n	[{'version': 'v1', 'created': 'Sat, 31 Mar 2007 03:16:14 GMT'}]	2007-05-23	[[Callan, David, ]]
4	704.0005	Alberto Torchinsky	Wael Abu-Shammala and Alberto Torchinsky	From dyadic $\Lambda_{\alpha}$ to $\Lambda_{\alpha}$	None	Illinois J. Math. 52 (2008) no.2, 681-689	None	None	math.CA math.FA	None	In this paper we show how to compute the $\Lambda_{\alpha}$ norm, $\alpha\ge\n0$, using the dyadic grid. This result is a consequence of the description of\nthe Hardy spaces $H^p(R^N)$ in terms of dyadic and special atoms.\n	[{'version': 'v1', 'created': 'Mon, 2 Apr 2007 18:09:58 GMT'}]	2013-10-15	[[Abu-Shammala, Wael, ], [Torchinsky, Alberto, ]]
5	704.0006	Yue Hin Pong	Y. H. Pong and C. K. Law	Bosonic characters of atomic Cooper pairs across resonance	6 pages, 4 figures, accepted by PRA	None	10.1103/PhysRevA.75.043613	None	cond-mat.mes-hall	None	We study the two-particle wave function of paired atoms in a Fermi gas with\ntunable interaction strengths controlled by Feshbach resonance. The Cooper pair\nwave function is examined for its bosonic characters, which is quantified by\nthe correction of Bose enhancement factor associated with the creation and\nannihilation composite particle operators. An example is given for a\nthree-dimensional uniform gas. Two definitions of Cooper pair wave function are\nexamined. One of which is chosen to reflect the off-diagonal long range order\n(ODLRO). Another one corresponds to a pair projection of a BCS state. On the\nside with negative scattering length, we found that paired atoms described by\nODLRO are more bosonic than the pair projected definition. It is also found\nthat at $(k_F a)^{-1} \ge 1$, both definitions give similar results, where more\nthan 90% of the atoms occupy the corresponding molecular condensates.\n	[{'version': 'v1', 'created': 'Sat, 31 Mar 2007 04:24:59 GMT'}]	2015-05-13	[[Pong, Y. H., ], [Law, C. K., ]]
6	704.0007	Alejandro Corichi	Alejandro Corichi, Tatjana Vukasinac and Jose A. Zapata	Polymer Quantum Mechanics and its Continuum Limit	16 pages, no figures. Typos corrected to match published version	Phys.Rev.D76:044016,2007	10.1103/PhysRevD.76.044016	IGPG-07/03-2	gr-qc	None	A rather non-standard quantum representation of the canonical commutation\nrelations of quantum mechanics systems, known as the polymer representation has\ngained some attention in recent years, due to its possible relation with Planck\nscale physics. In particular, this approach has been followed in a symmetric\nsector of loop quantum gravity known as loop quantum cosmology. Here we explore\ndifferent aspects of the relation between the ordinary Schroedinger theory and\nthe polymer description. The paper has two parts. In the first one, we derive\nthe polymer quantum mechanics starting from the ordinary Schroedinger theory\nand show that the polymer description arises as an appropriate limit. In the\nsecond part we consider the continuum limit of this theory, namely, the reverse\nprocess in which one starts from the discrete theory and tries to recover back\nthe ordinary Schroedinger quantum mechanics. We consider several examples of\ninterest, including the harmonic oscillator, the free particle and a simple\ncosmological model.\n	[{'version': 'v1', 'created': 'Sat, 31 Mar 2007 04:27:22 GMT'}, {'version': 'v2', 'created': 'Wed, 22 Aug 2007 22:42:11 GMT'}]	2008-11-26	[[Corichi, Alejandro, ], [Vukasinac, Tatjana, ], [Zapata, Jose A., ]]
7	704.0008	Damian Swift	Damian C. Swift	Numerical solution of shock and ramp compression for general material\n properties	Minor corrections	Journal of Applied Physics, vol 104, 073536 (2008)	10.1063/1.2975338	LA-UR-07-2051, LLNL-JRNL-410358	cond-mat.mtrl-sci	http://arxiv.org/licenses/nonexclusive-distrib/1.0/	A general formulation was developed to represent material models for\napplications in dynamic loading. Numerical methods were devised to calculate\nresponse to shock and ramp compression, and ramp decompression, generalizing\nprevious solutions for scalar equations of state. The numerical methods were\nfound to be flexible and robust, and matched analytic results to a high\naccuracy. The basic ramp and shock solution methods were coupled to solve for\ncomposite deformation paths, such as shock-induced impacts, and shock\ninteractions with a planar interface between different materials. These\ncalculations capture much of the physics of typical material dynamics\nexperiments, without requiring spatially-resolving simulations. Example\ncalculations were made of loading histories in metals, illustrating the effects\nof plastic work on the temperatures induced in quasi-isentropic and\nshock-release experiments, and the effect of a phase transition.\n	[{'version': 'v1', 'created': 'Sat, 31 Mar 2007 04:47:20 GMT'}, {'version': 'v2', 'created': 'Thu, 10 Apr 2008 08:42:28 GMT'}, {'version': 'v3', 'created': 'Tue, 1 Jul 2008 18:54:28 GMT'}]	2009-02-05	[[Swift, Damian C., ]]
8	704.0009	Paul Harvey	Paul Harvey, Bruno Merin, Tracy L. Huard, Luisa M. Rebull, Nicholas\n Chapman, Neal J. Evans II, Philip C. Myers	The Spitzer c2d Survey of Large, Nearby, Insterstellar Clouds. IX. The\n Serpens YSO Population As Observed With IRAC and MIPS	None	Astrophys.J.663:1149-1173,2007	10.1086/518646	None	astro-ph	None	We discuss the results from the combined IRAC and MIPS c2d Spitzer Legacy\nobservations of the Serpens star-forming region. In particular we present a set\nof criteria for isolating bona fide young stellar objects, YSO's, from the\nextensive background contamination by extra-galactic objects. We then discuss\nthe properties of the resulting high confidence set of YSO's. We find 235 such\nobjects in the 0.85 deg^2 field that was covered with both IRAC and MIPS. An\nadditional set of 51 lower confidence YSO's outside this area is identified\nfrom the MIPS data combined with 2MASS photometry. We describe two sets of\nresults, color-color diagrams to compare our observed source properties with\nthose of theoretical models for star/disk/envelope systems and our own modeling\nof the subset of our objects that appear to be star+disks. These objects\nexhibit a very wide range of disk properties, from many that can be fit with\nactively accreting disks to some with both passive disks and even possibly\ndebris disks. We find that the luminosity function of YSO's in Serpens extends\ndown to at least a few x .001 Lsun or lower for an assumed distance of 260 pc.\nThe lower limit may be set by our inability to distinguish YSO's from\nextra-galactic sources more than by the lack of YSO's at very low luminosities.\nA spatial clustering analysis shows that the nominally less-evolved YSO's are\nmore highly clustered than the later stages and that the background\nextra-galactic population can be fit by the same two-point correlation function\nas seen in other extra-galactic studies. We also present a table of matches\nbetween several previous infrared and X-ray studies of the Serpens YSO\npopulation and our Spitzer data set.\n	[{'version': 'v1', 'created': 'Mon, 2 Apr 2007 19:41:34 GMT'}]	2010-03-18	[[Harvey, Paul, ], [Merin, Bruno, ], [Huard, Tracy L., ], [Rebull, Luisa M., ], [Chapman, Nicholas, ], [Evans, Neal J., II], [Myers, Philip C., ]]
9	704.0010	Sergei Ovchinnikov	Sergei Ovchinnikov	Partial cubes: structures, characterizations, and constructions	36 pages, 17 figures	None	None	None	math.CO	None	Partial cubes are isometric subgraphs of hypercubes. Structures on a graph\ndefined by means of semicubes, and Djokovi\'{c}'s and Winkler's relations play\nan important role in the theory of partial cubes. These structures are employed\nin the paper to characterize bipartite graphs and partial cubes of arbitrary\ndimension. New characterizations are established and new proofs of some known\nresults are given.\n The operations of Cartesian product and pasting, and expansion and\ncontraction processes are utilized in the paper to construct new partial cubes\nfrom old ones. In particular, the isometric and lattice dimensions of finite\npartial cubes obtained by means of these operations are calculated.\n	[{'version': 'v1', 'created': 'Sat, 31 Mar 2007 05:10:16 GMT'}]	2007-05-23	[[Ovchinnikov, Sergei, ]]

	id	submitter	authors	title	comments	journal-ref	doi	report-no	categories	license	abstract	versions	update_date	authors_parsed
19990	708.2139	R. Rajesh	Colm Connaughton, R. Rajesh, Oleg Zaboronski	Constant flux relation for aggregation models with desorption and\n fragmentation	5 pages 2 figures, To appear in Physica A	Physica A Vol. 384, pg 108 (2007).	10.1016/j.physa.2007.04.074	None	cond-mat.stat-mech	None	We study mass fluxes in aggregation models where mass transfer to large\nscales by aggregation occurs alongside desorption or fragmentation. Two models\nare considered. (1) A system of diffusing, aggregating particles with influx\nand outflux of particles (in-out model) (2) A system of diffusing aggregating\nparticles with fragmentation (chipping model). Both these models can exist in\nphases where probability distributions are power laws. In these power law\nphases, we argue that the two point correlation function should have a certain\nhomogeneity exponent. These arguments are based on the exact constant flux\nscaling valid for simple aggregation with input. Predictions are compared with\nMonte Carlo simulations.\n	[{'version': 'v1', 'created': 'Thu, 16 Aug 2007 05:45:23 GMT'}]	2009-11-13	[[Connaughton, Colm, ], [Rajesh, R., ], [Zaboronski, Oleg, ]]
19991	708.2140	Zorica Konstantinovic	Z Konstantinovic, M Garcia del Muro, X Batlle, and A Labarta, M.\n Varela	The nanostructural origin of the ac conductance in dielectric granular\n metals: the case study of Co_20(ZrO_2)_80	Available online at:\n http://scitation.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=APPLAB000091000005052108000001&idtype=cvips&gifs=yes	Appl. Phys. Lett. 91, 052108 (2007)	10.1063/1.2766858	None	cond-mat.mtrl-sci cond-mat.dis-nn	None	We show which is the nanostructure required in granular Co20(ZrO2)80 thin\nfilms to produce an ac response such as the one that is universally observed in\na very wide variety of dielectric materials. A bimodal size distribution of Co\nparticles yields randomly competing conductance channels which allow both\nthermally assisted tunneling through small particles and capacitive conductance\namong larger particles that are further apart. A model consisting on a simple\ncubic random resistance-capacitor network describes quantitatively the\nexperimental results as functions of temperature and frequency, and enables the\ndetermination of the microscopic parameters controlling the ac response of the\nsamples.\n	[{'version': 'v1', 'created': 'Thu, 16 Aug 2007 06:32:51 GMT'}]	2007-08-17	[[Konstantinovic, Z, ], [del Muro, M Garcia, ], [Batlle, X, ], [Labarta, A, ], [Varela, M., ]]
19992	708.2141	Shyamal Lakshminarayanan	Shyamal Lakshminarayanan	A model for exploring bird morphology	7 pages, 1 table, 3 figures	None	None	None	q-bio.OT	None	A simplified model of the bird skeleton along with elongation parameters for\nthe flight feathers is used to explore the diversity of bird shapes. Varying a\nsmall number of parameters simulates a wide range of observed bird silhouettes.\nThe model may serve to examine developmental factors involved, help museum\ncurators develop computational approaches to bird morphometry and has\napplications in computer generated illustration.\n	[{'version': 'v1', 'created': 'Thu, 16 Aug 2007 06:34:53 GMT'}]	2007-08-17	[[Lakshminarayanan, Shyamal, ]]
19993	708.2142	Minhsiu Hsieh	Min-Hsiu Hsieh, Igor Devetak and Todd Brun	General entanglement-assisted quantum error-correcting codes	7 pages, no figure	Phys. Rev. A 76, 062313 (2007)	10.1103/PhysRevA.76.062313	None	quant-ph	None	Entanglement-assisted quantum error-correcting codes (EAQECCs) make use of\npre-existing entanglement between the sender and receiver to boost the rate of\ntransmission. It is possible to construct an EAQECC from any classical linear\ncode, unlike standard QECCs which can only be constructed from dual-containing\ncodes. Operator quantum error-correcting codes (OQECCs) allow certain errors to\nbe corrected (or prevented) passively, reducing the complexity of the\ncorrection procedure. We combine these two extensions of standard quantum error\ncorrection into a unified entanglement-assisted quantum error correction\nformalism. This new scheme, which we call entanglement-assisted operator\nquantum error correction (EAOQEC), is the most general and powerful quantum\nerror-correcting technique known, retaining the advantages of both\nentanglement-assistance and passive correction. We present the formalism, show\nthe considerable freedom in constructing EAOQECCs from classical codes, and\ndemonstrate the construction with examples.\n	[{'version': 'v1', 'created': 'Thu, 16 Aug 2007 06:40:58 GMT'}]	2009-11-13	[[Hsieh, Min-Hsiu, ], [Devetak, Igor, ], [Brun, Todd, ]]
19994	708.2143	Yuan Xu	Yuan Xu, Shuai Wang and Ke Xia	Spin-transfer torques in anti-ferromagnetic metals from first principles	The paper has substantially been rewritten, 4 pages, 5 figures	Physical Review Letters, 100, 226602 (2008)	10.1103/PhysRevLett.100.226602	None	cond-mat.mtrl-sci	None	In spite of the absence of a macroscopic magnetic moment, an anti-ferromagnet\nis spin-polarized on an atomic scale. The electric current passing through a\nconducting anti-ferromagnet is polarized as well, leading to spin-transfer\ntorques when the order parameter is textured, such as in anti-ferromagnetic\nnon-collinear spin valves and domain walls. We report a first principles study\non the electronic transport properties of anti-ferromagnetic systems. The\ncurrent-induced spin torques acting on the magnetic moments are comparable with\nthose in conventional ferromagnetic materials, leading to measurable angular\nresistances and current-induced magnetization dynamics. In contrast to\nferromagnets, spin torques in anti-ferromagnets are very nonlocal. The torques\nacting far away from the center of an anti-ferromagnetic domain wall should\nfacilitate current-induced domain wall motion.\n	[{'version': 'v1', 'created': 'Thu, 16 Aug 2007 07:55:58 GMT'}, {'version': 'v2', 'created': 'Wed, 4 Jun 2008 02:22:57 GMT'}]	2009-09-29	[[Xu, Yuan, ], [Wang, Shuai, ], [Xia, Ke, ]]
19995	708.2144	Eric Woolgar	E. Woolgar	Some Applications of Ricci Flow in Physics	Minor corrections in Sections IV and VI. Invited talk at Theory\n Canada III meeting, June 2007; submitted to Proceedings. Dedicated to Rafael\n D Sorkin on the occasion of his 60th birthday	Can.J.Phys.86:645,2008	10.1139/P07-146	None	hep-th gr-qc math.DG	None	I discuss certain applications of the Ricci flow in physics. I first review\nhow it arises in the renormalization group (RG) flow of a nonlinear sigma\nmodel. I then review the concept of a Ricci soliton and recall how a soliton\nwas used to discuss the RG flow of mass in 2-dimensions. I then present recent\nresults obtained with Oliynyk on the flow of mass in higher dimensions. The\nfinal section discusses one way in which Ricci flow may arise in general\nrelativity, particularly for static metrics.\n	[{'version': 'v1', 'created': 'Thu, 16 Aug 2007 06:50:14 GMT'}, {'version': 'v2', 'created': 'Mon, 27 Aug 2007 04:52:23 GMT'}, {'version': 'v3', 'created': 'Mon, 31 Dec 2007 04:03:04 GMT'}]	2009-11-13	[[Woolgar, E., ]]
19996	708.2145	John Bulava	John Bulava, Robert Edwards, George Fleming, K. Jimmy Juge, Adam C.\n Lichtl, Nilmani Mathur, Colin Morningstar, David Richards, Stephen J. Wallace	Results and Frontiers in Lattice Baryon Spectroscopy	To appear in the proceedings for the VII Latin American Symposium of\n Nuclear Physics and Applications	AIP Conf.Proc.947:137-140,2007	10.1063/1.2813791	None	hep-lat	None	The Lattice Hadron Physics Collaboration (LHPC) baryon spectroscopy effort is\nreviewed. To date the LHPC has performed exploratory Lattice QCD calculations\nof the low-lying spectrum of Nucleon and Delta baryons. These calculations\ndemonstrate the effectiveness of our method by obtaining the masses of an\nunprecedented number of excited states with definite quantum numbers. Future\nwork of the project is outlined.\n	[{'version': 'v1', 'created': 'Thu, 16 Aug 2007 07:03:27 GMT'}]	2014-11-18	[[Bulava, John, ], [Edwards, Robert, ], [Fleming, George, ], [Juge, K. Jimmy, ], [Lichtl, Adam C., ], [Mathur, Nilmani, ], [Morningstar, Colin, ], [Richards, David, ], [Wallace, Stephen J., ]]
19997	708.2146	Kaptari Leonid	S. M. Dorkin (International University Dubna, Dubna), M. Beyer (Inst.\n of Phys. Univ. of Rostock), S. S. Semikh and L. P. Kaptari (Bogoliubov Lab.\n Theor. Phys., JINR, Dubna)	Two-Fermion Bound States within the Bethe-Salpeter Approach	32 pages, XIII Tables, 8 figures	FewBodySyst.42:1-32,2008	10.1007/s00601-008-0196-8	None	nucl-th hep-ph	None	To solve the spinor-spinor Bethe-Salpeter equation in Euclidean space we\npropose a novel method related to the use of hyperspherical harmonics. We\nsuggest an appropriate extension to form a new basis of spin-angular harmonics\nthat is suitable for a representation of the vertex functions. We present a\nnumerical algorithm to solve the Bethe-Salpeter equation and investigate in\ndetail the properties of the solution for the scalar, pseudoscalar and vector\nmeson exchange kernels including the stability of bound states. We also compare\nour results to the non relativistic ones and to the results given by light\nfront dynamics.\n	[{'version': 'v1', 'created': 'Thu, 16 Aug 2007 07:08:20 GMT'}]	2008-11-26	[[Dorkin, S. M., , International University Dubna, Dubna], [Beyer, M., , Inst.\n of Phys. Univ. of Rostock], [Semikh, S. S., , Bogoliubov Lab.\n Theor. Phys., JINR, Dubna], [Kaptari, L. P., , Bogoliubov Lab.\n Theor. Phys., JINR, Dubna]]
19998	708.2147	Dalius Balciunas	Dalius Balciunas	The logistic equation and a critique of the theory of natural selection	31 pages, 5 figures, appendix	None	None	None	q-bio.PE	None	Species coexistence is one of the central themes in modern ecology.\nCoexistence is a prerequisite of biological diversity. However, the question\narises how biodiversity can be reconciled with the statement of competition\ntheory, which asserts that competing species cannot coexist. To solve this\nproblem natural selection theory is rejected because it contradicts kinetic\nmodels of interacting populations. Biological evolution is presented as a\nprocess equivalent to a chemical reaction. The main point is that interactions\noccur between self-replicating units. Under these assumptions biodiversity is\npossible if and only if species are identical with respect to the patterns of\nenergy flow in which individuals are involved.\n	[{'version': 'v1', 'created': 'Thu, 16 Aug 2007 07:15:04 GMT'}]	2007-08-17	[[Balciunas, Dalius, ]]
19999	708.2148	Reza Nourafkan	R. Nourafkan and N. Nafari	Kondo lattice model at half-filling	11 pages, 5 figures	None	10.1088/0953-8984/20/25/255231	None	cond-mat.str-el	None	The single- and two-channel Kondo lattice model consisting of localized spins\ninteracting antiferromagnetically with the itinerent electrons, are studied\nusing dynamical mean field theory. As an impurity solver for the effective\nsingle impurity Anderson model we used the exact diagonalization (ED) method.\nUsing ED allowed us to perform calculations for low temperatures and couplings\nof arbitrary large strength. Our results for the single-channel case confirm\nand extend the recent investigations. In the two-channel case we find a\nsymmetry breaking phase transition with increasing coupling strength.\n	[{'version': 'v1', 'created': 'Thu, 16 Aug 2007 07:21:03 GMT'}]	2009-11-13	[[Nourafkan, R., ], [Nafari, N., ]]

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